5 citations · 5 across the 3 of their papers we have counts for
8 papers
UnDA: Unpaired Domain Alignment for Cross-Modal Knowledge Transfer in Medical Imaging
Rafsan Jany, Shadab Tanjeed Ahmad, Ahsan Bulbul +3
Multimodal based approaches often outperform single modality approaches in downstream tasks as the different modalities provide complementary information, yet acquiring paired clin…
SleepExplain: Explainable Non-Rapid Eye Movement and Rapid Eye Movement Sleep Stage Classification from EEG Signal
Rafsan Jany, Md. Hamjajul Ashmafee, Iqram Hussain +1
Classification of sleep stages is one of the most important diagnostic approaches for a variety of sleep-related disorders. Electroencephalography (EEG) is regarded as a powerful t…
Probabilistic Feature Imputation and Uncertainty-Aware Multimodal Federated Aggregation
Nafis Fuad Shahid, Maroof Ahmed, Md Akib Haider +3
Multimodal federated learning enables privacy-preserving collaborative model training across healthcare institutions. However, a fundamental challenge arises from modality heteroge…
Progressive Code Integration for Abstractive Bug Report Summarization
Shaira Sadia Karim, Abrar Mahmud Rahim, Lamia Alam +4
Bug reports are often unstructured and verbose, making it challenging for developers to efficiently comprehend software issues. Existing summarization approaches typically rely on…
Personalized Federated Segmentation with Shared Feature Aggregation and Boundary-Focused Calibration
Ishmam Tashdeed, Md. Atiqur Rahman, Sabrina Islam +1
Personalized federated learning (PFL) possesses the unique capability of preserving data confidentiality among clients while tackling the data heterogeneity problem of non-independ…
AntiFLipper: A Secure and Efficient Defense Against Label-Flipping Attacks in Federated Learning
Aashnan Rahman, Abid Hasan, Sherajul Arifin +5
Federated learning (FL) enables privacy-preserving model training by keeping data decentralized. However, it remains vulnerable to label-flipping attacks, where malicious clients m…